Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A computer-implemented method for increasing user engagement in a video conference, comprising: estimating a user engagement status of a first participant; identifying, based on the user engagement status, a second participant who has introduced a graphical notation; determining whether a correlation exists between the graphical notation and the video conference; prompting, when a correlation exists between the graphical notation and video conference, the second participant to share the graphical notation with the first participant; prompting, when a correlation exists between the graphical notation and the video conference, the first participant to view the graphical notation, wherein the correlation exists between the graphical notation and the video conference when a deviation between the graphical notation and a baseline is below a predefined threshold; and dynamically displaying, in response to an affirmative response from the second participant, the graphical notation to the first participant.
This invention relates to enhancing user engagement in video conferences by analyzing participant behavior and sharing relevant graphical notations. The method involves monitoring a first participant's engagement level, such as attention or interaction, and identifying a second participant who has introduced a graphical notation, such as a drawing, diagram, or annotation. The system determines whether the graphical notation is relevant to the ongoing video conference by assessing its correlation to the conference content. A correlation is established if the deviation between the notation and a predefined baseline (e.g., expected content or context) falls below a set threshold. If a correlation exists, the system prompts the second participant to share the notation with the first participant and encourages the first participant to view it. Upon the second participant's confirmation, the graphical notation is dynamically displayed to the first participant, fostering engagement and collaboration. The approach ensures that only relevant and contextually appropriate notations are shared, improving the efficiency and effectiveness of communication in video conferences.
2. The computer-implemented method of claim 1 , wherein introducing a graphical notation includes creating a graphical notation during the video conference.
This invention relates to enhancing video conferencing systems by dynamically introducing graphical notations during a live session. The technology addresses the challenge of effectively conveying information in real-time during virtual meetings, where traditional communication methods may lack clarity or interactivity. The method involves generating graphical notations, such as annotations, diagrams, or symbols, directly within the video conference interface. These notations can be created by participants or automated systems to highlight key points, illustrate concepts, or provide visual aids. The graphical notations are displayed in real-time to all participants, ensuring synchronized understanding and engagement. The system may also support collaborative editing, allowing multiple users to contribute to or modify the notations during the session. This approach improves communication efficiency, reduces ambiguity, and enhances the overall collaborative experience in virtual meetings. The invention is particularly useful in educational, business, and technical settings where visual aids are critical for effective communication.
3. The computer-implemented method of claim 1 , wherein the user engagement status is selected from a group comprising disinterest or confusion.
This invention relates to computer-implemented methods for analyzing user engagement with digital content, particularly focusing on detecting disinterest or confusion. The method involves monitoring user interactions with content, such as reading speed, scrolling behavior, or time spent on specific sections, to determine engagement levels. When the system identifies patterns indicative of disinterest (e.g., rapid scrolling, minimal time spent) or confusion (e.g., repeated revisiting of the same content, prolonged pauses), it triggers adaptive responses. These responses may include modifying the content presentation, providing additional explanatory material, or prompting user feedback to clarify their experience. The system may also use machine learning models trained on historical engagement data to refine its detection accuracy over time. The goal is to improve user experience by dynamically addressing engagement issues in real-time, ensuring content remains accessible and comprehensible. This approach is particularly useful in educational platforms, customer support interfaces, or any digital environment where user retention and comprehension are critical.
4. The computer-implemented method of claim 1 , further comprising deriving the deviation, wherein the deriving includes performing a clustering technique.
This invention relates to a computer-implemented method for analyzing data to identify deviations, particularly in large datasets where patterns or anomalies need to be detected. The method addresses the challenge of efficiently processing and interpreting complex data to uncover meaningful deviations that may indicate errors, trends, or other significant information. The method involves collecting data from one or more sources and preprocessing it to prepare for analysis. This preprocessing may include cleaning, normalization, or transformation of the data to ensure consistency and accuracy. Once prepared, the data is analyzed to identify deviations, which are differences or anomalies compared to expected or baseline values. A key aspect of this method is the use of clustering techniques to derive these deviations. Clustering groups similar data points together, allowing the system to identify outliers or deviations that do not fit within the expected clusters. This approach enhances the accuracy and reliability of deviation detection by leveraging statistical and machine learning methods to distinguish between normal and abnormal data patterns. The method may also include additional steps such as validating the detected deviations, generating reports, or triggering automated actions based on the results. The use of clustering techniques ensures that the deviations are derived in a systematic and scalable manner, making the method suitable for applications in fields such as fraud detection, quality control, and predictive maintenance.
5. The computer-implemented method of claim 1 , wherein the baseline is derived based on one or more images.
This invention relates to computer-implemented methods for deriving a baseline from one or more images, particularly in the context of analyzing data to detect deviations or changes. The method addresses the challenge of establishing a reliable reference point (baseline) for comparison against subsequent data, which is critical in applications such as medical imaging, environmental monitoring, or industrial quality control. The baseline is generated by processing one or more images to extract relevant features or patterns, which serve as a standard for future comparisons. This allows for accurate detection of anomalies, trends, or deviations over time. The method may involve techniques such as image segmentation, feature extraction, or statistical analysis to ensure the baseline is representative and robust. By using multiple images, the method improves accuracy and reliability compared to single-image baselines. The derived baseline can then be used in subsequent steps to compare against new data, enabling automated monitoring, diagnostics, or decision-making processes. The invention enhances the precision and efficiency of systems that rely on image-based comparisons, reducing human intervention and improving consistency.
Unknown
October 27, 2020
Browse 5M+ US patents with plain-English claim translations and AI-generated analysis.